@article{Silver2016Mastering,
  title={Mastering the game of {Go} with deep neural networks and tree search},
  author={Silver, David and Huang, Aja and Maddison, Chris J. and Guez, Arthur and Demis Hassabis},
  journal={Nature},
  volume={529},
  number={7587},
  pages={484-489},
  year={2016},
}

@article{Mnih2015Human,
	title={Human-level control through deep reinforcement learning},
	author={Mnih, Volodymyr and Kavukcuoglu, Koray and Silver, David and Rusu, Andrei A. and Veness, Joel and Bellemare, Marc G. and Graves, Alex and Riedmiller, Martin and Fidjeland, Andreas K. and Ostrovski, Georg},
	journal={Nature},
	volume={518},
	number={7540},
	pages={529},
	year={2015},
}

@InProceedings{pmlr-v48-mniha16,
	title = 	 {Asynchronous Methods for Deep Reinforcement Learning},
	author = 	 {Volodymyr Mnih and Adria Puigdomenech Badia and Mehdi Mirza and Alex Graves and Timothy Lillicrap and Tim Harley and David Silver and Koray Kavukcuoglu},
	booktitle = 	 {Proceedings of The 33rd International Conference on Machine Learning},
	pages = 	 {1928--1937},
	year = 	 {2016},
	editor = 	 {Maria Florina Balcan and Kilian Q. Weinberger},
	volume = 	 {48},
	series = 	 {Proceedings of Machine Learning Research},
	address = 	 {New York, New York, USA},
	month = 	 {20--22 Jun},
	publisher = 	 {PMLR},
	pdf = 	 {http://proceedings.mlr.press/v48/mniha16.pdf},
	url = 	 {http://proceedings.mlr.press/v48/mniha16.html},
	abstract = 	 {We propose a conceptually simple and lightweight framework for deep reinforcement learning that uses asynchronous gradient descent for optimization of deep neural network controllers. We present asynchronous variants of four standard reinforcement learning algorithms and show that parallel actor-learners have a stabilizing effect on training allowing all four methods to successfully train neural network controllers. The best performing method, an asynchronous variant of actor-critic, surpasses the current state-of-the-art on the Atari domain while training for half the time on a single multi-core CPU instead of a GPU. Furthermore, we show that asynchronous actor-critic succeeds on a wide variety of continuous motor control problems as well as on a new task of navigating random 3D mazes using a visual input.}
}